Abstract—One of the most crucial problem in data mining is association rule mining. It requires large computation and I/O traffic capacity. One approach to resolve this problem is the use of distributed data mining algorithms in grid. It offers an effective way to mine for large data sets. Therefore, we implemented distributed data mining with Apriori algorithm in grid environment. However, usage of grid environment raises some issues about the optimization of the Apriori algorithm, especially the cost of the node to node communication and data distribution. In this paper, an Optimized Distributed Association rule mining approach for geographically distributed data is introduced in parallel and distributed environment; therefore, it reduces communication costs.
Index Terms—Data Mining; Apriori Algorithm; Grid Environment; Distributed Computing.
M. A. Mottalib, M. M. Islam, Md. A. Rahman, and S. A. Abeer are with Dept. of Computing and Information Technology, Islamic University of Technology, Gazipur, Bangladesh
K. S. Arefin is with Dept. of Computer Science and Engineering, University of Asia Pacific, Dhaka, Bangladesh
e-mail: mottalib@iut-dhaka.edu, {arefin, majhar999}@uap-bd.edu, {arif.rah, sabbeer.iut}@gmail.com
Cite: M. A. Mottalib, Kazi Shamsul Arefin, Mohammad Majharul Islam, Md. Arif Rahman, and Sabbeer Ahmed Abeer, "Performance Analysis of Distributed Association Rule Mining with Apriori Algorithm," International Journal of Computer Theory and Engineering vol. 3, no. 4, pp. 484-488, 2011.
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